Toys have been around for thousands of years. Egyptian, Grecian, and Roman children played with toys that were made from stone, pottery, wax, wood, and other primitive materials. More recently, toys have also been made of newer materials such as plastics. These toys, however, were static and children were left to use their imagination in forming animations or personalities for the toys. Other toys have included mechanical features that allowed for simple mechanical movements or for the recitation of a word or phrase when the child pulled a string or pressed a button.
With the proliferation of computers, actuators, and processing technology, interactive toys and computer games have become more common. These toys are capable of sensing the environment, making decisions, and interacting with children. However, many of the toys only provide for a limited set of simple linear interactions. Creating more sophisticated content for these toys and games is still difficult as there are many potential inputs, each potentially requiring a different response.
Creating systems that can take these inputs and make decisions, reason, evolve, communicate, and manipulate objects is widely studied in branches of computer science and robotics. While some current toys have more interactive features, these toys still lack various personality traits found in humans. Creating a synthetic character having various personality traits is even more difficult. Traditional tools for creating scripts and content are too simplistic to allow for the efficient creation of complex interactive content. For example, common script writing tools are often linear and do not facilitate dynamic interactions. As such, there are a number of challenges and inefficiencies found in traditional tools for creating content for artificial intelligence systems such as toys and games.